Calculating value of a customer
AI’s client, a national chain of fitness centers, has over 100,000 members distributed across the United States in major metropolitan centers including New York City, Los Angeles, San Francisco, Miami, Chicago, and Atlanta. For the client, attracting, engaging, and retaining appropriate customers is critical for viability and for profitability. The client employed Audacious Inquiry to assess how it could improve these key business variables.
Our assessment of key business variables was two-tiered: the AI team performed a qualitative analysis through management interviews and member focus groups; at the same time, the team undertook a quantitative analysis by analyzing member cohorts using existing information in the member database. In executing our analysis, we assumed a simplified member lifecycle of attract, engage, retain, and defect.
For the qualitative analysis, the goal was to uncover important customer touch-points and areas of satisfaction and dissatisfaction with the gym. AI team members conducted personal interviews with the general managers from all fourteen New York City locations. The interviews focused on managers’ perspectives on acquisition, engagement, retention, and other relevant issues. Two focus group meetings with current members were also conducted.
For the quantitative analysis, the goal was to understand local drivers of acquisition, engagement, and retention and to determine the need for more data and/or new key performance indicators (KPIs). In order to do this, AI dug into several years’ of customer data, performing exploratory analyses around the key Customer Lifetime Value (CLV) metrics identified. Necessary data sets were compiled, focusing both on the number of members over time and on member characteristics. Using this data, both segment-level and individual-level models were executed.
Following a research period, key insights from management interviews and focus groups were identified and model results were analyzed. The findings were merged and interpreted into important results and presented to senior executives. Significant novel correlations were discovered in the following areas: retention and club usage, retention and frequency of visits, payment plans and customer loyalty, and membership types and customer loyalty.